Synovial sarcoma (SS) is an aggressive cancer occurring mainly in young adults that contains in >95% of[unreadable] cases a t(X;18) fusing SYT to either SSX1 or SSX2. The chimeric SYT-SSX product appears to function as[unreadable] an aberrant transcriptional protein to deregulate gene expression but its critical target genes remain[unreadable] unknown. In Project 4, we plan to integrate our existing Affymetrix expression profiling data with RNA[unreadable] interference (RNAi), chromatin immunoprecipitation (ChrIP), bioinformatics, and re-sequencing to gain[unreadable] insights into SS pathogenesis and to identify new methods for prognostication and targeted therapy. Aim 1.[unreadable] Analysis of signaling pathways in SS. Leads provided by our expression profiling data into signaling[unreadable] pathways involved in the biology of SS will be pursued, including the SHH/GLI, Wnt/beta-catenin, and[unreadable] selected kinase pathways. Functional and mutational studies of these pathways will be performed and the[unreadable] expression profiles associated with their activation will be determined. Aim 2. Analysis of SYT-SSX-regulated[unreadable] gene expression. To define the targets of SYT-SSX in SS, we will perform expression profiling of SYT-SSX[unreadable] knockdown in SS cell lines and ChrIP analysis of candidate SYT-SSX targets. We will also use bioinformatic[unreadable] approaches to identify recurrent motifs in the promoters of candidate SYT-SSX target genes drawn from the[unreadable] same two sources. Such motifs might provide leads in identifying transcription factor families that interact[unreadable] with SYT-SSX and mediate its effects. SYT-SSX target genes will then be validated as transcriptional[unreadable] targets. Finally, selected SYT-SSX target genes will be evaluated as potential therapeutic targets by[unreadable] assessing their role in SS growth using RNAi knockdown. Aim 3. Development of expression profiling-based[unreadable] clinical predictors in SS. Two approaches will be used to identify prognostically significant genes within the[unreadable] expression profile of SS, using existing and prospective microarray data. First, a predictor of distant[unreadable] recurrence-free survival will be developed and then combined with a new nomogram predictor based on[unreadable] clinical variables. Secondly, the expression signature of metastatic potential will be defined based on[unreadable] metastatic and non-metastatic SS samples and used to develop a prediction model for metastatic potential.[unreadable] The genes composing these predictors may provide insights into the determinants of clinical behavior in SS[unreadable] and opportunities for improved assignment of SS patients into high risk and low risk subgroups.